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GCP Core Services Overview (GCP PCA) Flashcards
GCP Professional Cloud Architect Flashcards
Study our GCP Core Services Overview (GCP PCA) flashcards for the GCP Professional Cloud Architect exam with 35+ flashcards. View as flashcards, a searchable table, or as a fun matching game.
| Front | Back |
| Compare App Engine and Kubernetes Engine | App Engine is fully managed and auto-scales while Kubernetes Engine provides container orchestration and more granular control |
| How does App Engine assist in development workflows | Offers SDKs and APIs for rapid application development and deployment |
| How does Cloud Functions support developers | Supports multiple programming languages and automatically scales with usage |
| What are Google Cloud Functions | Event-driven serverless compute service for lightweight single-purpose functions |
| What differentiates Cloud Functions from App Engine | Cloud Functions is event-driven while App Engine is request-driven |
| What feature of App Engine simplifies database interactions | Integration with managed services like Cloud SQL and Firestore |
| What is a benefit of using Cloud Functions for prototypes | Simplifies creating and testing small features without managing infra structures |
| What is a benefit of using Kubernetes Engine over Compute Engine | Simplifies container orchestration with built-in scaling and networking |
| What is a common use case for Cloud Functions | Responding to events such as Cloud Storage updates or Pub/Sub messages |
| What is a common use case for Google Compute Engine in machine learning | Hosting custom ML models or running large-scale ML processing jobs |
| What is a key advantage of running workloads on App Engine | Removes operational overhead with built-in monitoring and health management |
| What is a key benefit of Cloud Run | Able to run any containerized application without infrastructure management |
| What is a key feature of Google App Engine | Automatic scaling based on traffic |
| What is a key similarity between Cloud Run and Kubernetes Engine | Both support containerized workloads, but Cloud Run is serverless |
| What is a primary advantage of Google Compute Engine | Fine-grained control over virtual machines including custom machine types |
| What is a primary use case of Google Compute Engine | Hosting applications or running batch processing jobs |
| What is a primary use case of Google Kubernetes Engine | Orchestrating and managing containers in production |
| What is a security feature of Kubernetes Engine | Built-in Identity and Access Management (IAM) integration for secure workloads |
| What is an example of an App Engine use case | Deploying a web application with fluctuating user traffic |
| What is Google App Engine | A fully managed platform for building and deploying applications |
| What is Google Cloud Run | Managed service to run containers in a serverless environment |
| What is Google Compute Engine | Scalable virtual machines for running workloads on GCP |
| What is Google Kubernetes Engine | Managed Kubernetes service for deploying containerized applications |
| What is the pricing model of Google Cloud Run | Pay only for the exact resources consumed during request processing |
| What is the role of Kubernetes Engine in modernization | Helps migrate legacy applications to containerized environments for better scalability |
| What languages and runtimes are supported by Cloud Functions | JavaScript, Python, Go, Java, and more |
| What makes Kubernetes Engine suitable for production | High availability, multi-cluster support, and automatic upgrades |
| What type of event triggers a Cloud Function | Events such as HTTP requests, Pub/Sub messages, or Cloud Storage changes |
| What type of workload is ideal for Cloud Run | Stateless containerized applications with rapid scaling needs |
| When to use Google App Engine | For building scalable web or mobile backends without worrying about infrastructure |
| When to use Google Cloud Functions | For lightweight, event-driven compute tasks with minimal setup |
| When to use Google Cloud Run | When running stateless containerized workloads with serverless scalability |
| When to use Google Compute Engine | When you need direct control over virtual machines for custom configurations |
| When to use Google Kubernetes Engine | When you need to manage and orchestrate containerized workloads |
| When to use Kubernetes Engine as opposed to App Engine | When you need control over container orchestration and custom deployment configurations |
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About the Flashcards
Flashcards for the GCP Professional Cloud Architect exam cover the core Google Cloud compute services students must recognize on test day. Each card defines services like Compute Engine virtual machines, App Engine's fully managed platform, Kubernetes Engine container orchestration, event-driven Cloud Functions, and serverless Cloud Run, linking names to purposes and primary advantages.
A second pass helps you decide when to choose each option by highlighting scaling behavior, pricing, security, and use-case guidelines. Side-by-side comparisons reinforce distinctions-such as event versus request workflows or VM control versus managed platforms-so you can swiftly answer scenario questions and recall key terminology during the timed assessment.
Topics covered in this flashcard deck:
- Compute Engine virtual machines
- App Engine platform
- Kubernetes Engine containers
- Cloud Functions event triggers
- Cloud Run serverless containers
- Service selection scenarios